MIRI_AB2Slice

class jwst.transforms.MIRI_AB2Slice(beta_zero=Parameter('beta_zero', value=0.0), beta_del=Parameter('beta_del', value=1.0), channel=Parameter('channel', value=1.0), **kwargs)[source]

Bases: astropy.modeling.core.Model

MIRI MRS alpha, beta to slice transform

Parameters

Attributes Summary

beta_del

Beta_del parameter

beta_zero

Beta_zero parameter

channel

one of 1, 2, 3, 4

fittable

n_inputs

The number of inputs.

n_outputs

The number of outputs.

param_names

Names of the parameters that describe models of this type.

standard_broadcasting

Methods Summary

__call__(*inputs[, model_set_axis, …])

Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.

evaluate(beta, beta_zero, beta_del, channel)

Evaluate the model on some input variables.

Attributes Documentation

beta_del = Parameter('beta_del', value=1.0)

Beta_del parameter

beta_zero = Parameter('beta_zero', value=0.0)

Beta_zero parameter

channel = Parameter('channel', value=1.0)

one of 1, 2, 3, 4

Type

MIRI MRS channel

fittable = False
n_inputs = 1

The number of inputs.

n_outputs = 1

The number of outputs.

param_names = ('beta_zero', 'beta_del', 'channel')

Names of the parameters that describe models of this type.

The parameters in this tuple are in the same order they should be passed in when initializing a model of a specific type. Some types of models, such as polynomial models, have a different number of parameters depending on some other property of the model, such as the degree.

When defining a custom model class the value of this attribute is automatically set by the Parameter attributes defined in the class body.

standard_broadcasting = False

Methods Documentation

__call__(*inputs, model_set_axis=None, with_bounding_box=False, fill_value=nan, equivalencies=None, inputs_map=None, **new_inputs)

Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.

static evaluate(beta, beta_zero, beta_del, channel)[source]

Evaluate the model on some input variables.